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Neo4j GraphTalks
• 09:00-09:30 Frühstück und Networking
• 09:30-10:00 Einführung in Graph-Datenbanken und Neo4j (Bruno Ungermann, Neo Technology)
• 10.00-11.00 Semantic Data Management – der Weg zu einer nachhaltigen unternehmensweiten Datenplattform (Dr. Andreas Weber, semantic PDM)
• Open End (semantic PDM, Neo Technology)
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Complexity
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The Internet (oT)
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Domain Model Logistics Process
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Traditional Approach: Fixed Schema, Tables
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Graph Model: Nodes & Relationships
Container Load
USING ROUTEDepart 2014-04-15Arrive 2014-04-28
FROM
TO
TO
FROM
USING ROUTE
Depart 2014-04-15
Arrive 2014-04-28
IN
IN
EMISSION
FUELING
USING VESSEL
USING_CARRIER
LOAD
LOAD
PART_OF
USING CARRIER
Vessel
Physical Container
Container Load
ShipmentCarrier
EmissionClass A
Shipment
Carrier
Route10520km
Route823km
FuelingMax Wgt 80Type Gas B
Town:Tokyo
Town:Hong Kong
Town:Hamburg
Container LoadContainer
LoadContainer LoadParcel Weight 15.5kg
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Intuitiveness
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A Naturally Adaptive Model vs Fixed Schema
Flexibility
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“We found Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10-100 times less code. Today, Neo4j
provides eBay with functionality that was previously impossible.”- Volker Pacher, Senior Developer
“Minutes to milliseconds” performanceQueries up to 1000x faster than other tested database
types
Speed
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Discrete DataMinimally
connected data
Neo4j is designed for data relationships
Other NoSQL
Relational DBMS Neo4j Graph DB
Connected DataFocused on
Data Relationships
Development BenefitsEasy model maintenance
Easy query
Deployment BenefitsUltra high performanceMinimal resource usage
Use the Right Database for the Right Job
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2000 2003 2007 2009 2011 2013 2014 20152012
GraphConnect, first conference for
graph DBsFirst
Global 2000 Customer
Introduced first and only declarative
query language for property
graph
Published O’Reilly
bookon Graph
Databases
First native
graph DB in 24/7
production
Invented property
graph model
Contributed first graph DB to open
source
Extended
graph data
model to labeled property
graph
150+ customers
50K+ monthlydownloads500+ graph DB eventsworldwide
Neo4j: The Graph Database Leader
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SOFTWARE FINANCE RETAIL MANUFACTURING more
SOCIAL TELECOMMEDIA HEALTHCA
RE
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2012 2015
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“Forrester estimates that over 25% of enterprises will be using graph databases by 2017”
“Neo4j is the current market leader in graph databases.”
“Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-
driven operations and decisions after the design of data capture.”
IT Market Clock for Database Management Systems, 2014https://www.gartner.com/doc/2852717/it-market-clock-database-management
TechRadar™: Enterprise DBMS, Q1 2014http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801
Graph Databases – and Their Potential to Transform How We Capture Interdependencies (Enterprise Management Associates)http://blogs.enterprisemanagement.com/dennisdrogseth/2013/11/06/graph-databasesand-potential-transform-capture-interdependencies/
Neo4j Leads the Graph Database Revolution
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Graph Based Success
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Real-Time Recommendati
ons
Fraud Detection
Network & IT
Operations
Knowledge Manageme
ntGraph Based Search
Identity & Access
Management
Common Graph Use Cases
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Knowledge Management: Status Quo
Dr. Andreas Weber | semantic data management | 11.11.2016
QS / LIMS
ERP
LogistikWarehouse-
managementProdukt-
management
TechnischesPDM/PLM
Dokumenten-management
Excel
Excel Powerpoint
Powerpoint
Excel
Excel
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Logistik
RDBMS CRM
RDBMS
Mails
Mailsyst
Dokumente
Filesystem
Media Library
Filesysem
CMS
RDBMS
Social
RDBMS
LogFiles
RDBMS
Ecommerce
RDBMS
Graph Based Knowledge Management (MDM, Enterprise Search..)
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Adidas Shared Meta Data Service
20 Knowledge Management
Background• Global leader in sporting goods industry
services firm footware, apparel, hardware, 14.5 bln sales, 53,000 people
• Multitude of products, markets, media, assets and audiences
Business Problem • Beset by a wide array of information silos
including data about products, markets, social media, master data, digital assets, brand content and more
• Provide the most compelling and relevant content to consumers
• Offering enhanced recommendations to drive revenue
Solution and Benefits• Save time and cost through stadardized access
to content sharing-system with internal teams, partners, IT units, fast, reliable, searchable avoiding reduandancy
• Inprove customer experience and increase revenue by providing relevant content and recommentations
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Background• Mid-size German insurer founded in 1858• Project executed by Delvin, a subsidiary
of die Bayerische Versicherung and an IT insurance specialist
Business Problem• Field sales needed easy, dynamic, 24/7
access to policies and customer data• Existing DB2 system unable to meet
performance and scaling demands
Solution and Benefits• Enabled flexible searching of policies and
associated personal data• Raised the bar on industry practices• Delivered high performance and scalability • Ported existing metadata easily
Die Bayerische Versicherung INSURANCE
Knowledge Management21
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Background• Leading European Airline • 100+ mln passengers • 2+ mln tons freight per year • 700+ aircrafts
Business Problem• Need for flexible high performant Inflight
Asset Management, onboard entertainment, byod
• Complex data set: CMDB, CMS, Aircraft data feed, media library
• Maintain individual configuration for each Aircraft
• Complex data model, aircrafts, hardware, vitual containers, licenses, business rules, versions, content ...
Solution and Benefits• Neo4j powers integrated platform that
provides fast access to all aspects needed to maintain complex system
• Fast implementation• Higly flexible data model enable constant
evolution
Lufthansa Digital Asset Mangagement
22 Graph Based Search, Knowledge Managment
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Background• Toy Manufacturer, founded 80+ years ago,
plastic figurines sold in 50+ countries• 100 Mio, 250 employees• Production Process in different countries like
China• Polymer Processing, Children‘s toys, high
responsibility
Business Problem• Product related data stored in many different
data stores including SAP, Navision, Laboratory Systems, Document Systems, Powerpoint, Excel..
• Hard to find correct answers for authorities, , internally, parents
Solution and Benefits• Neo4j powers integrated platform that
provides visibility across whole supply chain• Domain Experts create and evolve data model• Correct answers within seconds
Schleich Product Information Management
23 Knowledge Management
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Related products
People who bought Xalso bought Y
The mainproduct
Recommendations (In Real-Time)
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LOOKS_AT
KITCHEN AID
SERIES
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LOOKS_AT
Returns
Purchase History
Price-range
Home delivery
Inventory
Express goods
Complaints
reviews
TweetsEmails
Category
Promotions
Bundling
Location
KITCHEN AID
SERIES
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Business Problem• Optimize walmart.com user experience• Connect complex buyer and product data to
gain super-fast insight into customer needs and product trends
• RDBMS couldn’t handle complex queries
Solution and Benefits• Replaced complex batch process real-time
online recommendations• Built simple, real-time recommendation
system with low-latency queries• Serve better and faster recommendations by
combining historical and session data
Background
• Founded in 1962 and based in Arkansas• 11,000+ stores in 27 countries with
walmart.com online store• 2M+ employees and $470 billion in annual
revenues
Walmart RETAIL
Real-Time Recommendations28
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Background• One of the world’s largest logistics carriers• Projected to outgrow capacity of old system• New parcel routing system
Single source of truth for entire networkB2C and B2B parcel trackingReal-time routing: up to 7M parcels per day
Business Problem• Needed 365x24x7 availability• Peak loads of 3000+ parcels per second• Complex and diverse software stack• Need predictable performance, linear
scalability• Daily changes to logistics network: route from
any point to any point
Solution and Benefits• Ideal domain fit: a logistics network is a graph • Extreme availability, performance via
clustering• Greatly simplified routing queries vs. relational• Flexible data model reflect real-world data
variance much better than relational• Whiteboard-friendly model easy to
understand
Accenture LOGISTICS
29 Real-Time Routing Recommendations
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Background• San Jose-based communications equipment
giant ranks #91 in the Global 2000 with $44B in annual sales
• Needed real-time recommendations to encourage knowledge base use on company’s support portal
Solution and Benefits• Faster problem resolution for customers and
decreased reliance on support teams• Scrape cases, solutions, articles et al
continuously for cross-reference links• Provide real-time reading recommendations• Uses Neo4j Enterprise HA cluster
Business Problem• Reduce call-center volumes and costs via
improved online self-service quality• Leverage large amounts of knowledge stored
in service cases, solutions, articles, forums, etc.
• Reduce resolution times and support costs
Cisco COMMUNICATIONS
Real-Time Recommendations
SolutionSupportCase
SupportCase
Knowledge Base
Article
Message
Knowledge Base
Article
Knowledge Base
Article
30
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Business Problem• Extremly complex individual pricing
calculations• Moved from per month to per day calculation• Former system too slow, too inflexible
Solution and Benefits• Huge performance increase through
replacement of legacy system• 4 Core Laptop, 6% CPU usage provides better
performance than 3 server 96 Core config with 80% CPU usage „mind-blowing“
• Overcame internal hurdles by using embedded, application internal cache vs new database system
Background
• Largest Hospitality company worldwide• 4.500+ hotels 6.500 700.000 rooms 1.5
Mln • 15 Bln eCommerce Sales 2015, #7 IDC rating
internet sales
Marriott Hospitality
Real-Time Recommendations31
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MeshRouterGatew
ay
Router
Router
Router
MeshRouter
Router
Router
MeshRouterGatew
ay
AccessPoint
CPU
CPU CPU
CPU
Mobile
Mobile Mobile
Mobile
Base Station
CPU
CPU
CPU
CPU
Access Point
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Background• Second largest communications company
in France• Based in Paris, part of Vivendi Group,
partnering with Vodafone
Solution and Benefits• Flexible inventory management supports
modeling, aggregation, troubleshooting• Single source of truth for entire network• New apps model network via near-1:1
mapping between graph and real world• Schema adapts to changing needs
Network and IT Operations
SFR COMMUNICATIONS
Business Problem• Infrastructure maintenance took week to
plan due to need to model network impacts• Needed what-if to model unplanned outages• Identify network weaknesses to uncover
need for additional redundancy• Info lived on 30+ systems, with daily
changes
LINKED
LINKED
LINKED
DEPENDS_ON
Router Service
Switch Switch
Router
Fiber Link Fiber Link
Fiber Link
Oceanfloor Cable
34
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Business Problem• Original RDBMS solution could handle only
5,000 servers• Improve net performance company-wide• Leverage M&A legacy systems with no room
for error
Solution and Benefits• Store UNIX server and network config in Neo4j• Combine Splunk log data into an application
that visualizes events on the network• Neo4j vastly improved app performance• New apps built much faster with Neo4j than
SQL
Large Investment Bank FINANCIAL SERVICES
Network and IT Operations35
Background• One of the world’s oldest and largest banks• 100+ year-old bank with more than 1000
predecessor institutions• 500,000 employees and contractors• Needed to manage and visualize ~50,000
Unix servers in its network
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Identity Relationship ManagementIdentity Access Management
Applications and data
Endpoints
People
Customers(millions)
Partners and Suppliers
Workforce(thousands)
PCs Tablets
On-premises Private Cloud
Public Cloud
Things(Tens of millions)
WearablesPhones
PCs
Customers(millions)
On-premises
Applications and data
Endpoints
People
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Background• Oslo-based telcom provider is #1 in Nordic
countries and #10 in world• Online, mission-critical, self-serve system
lets users manage subscriptions and plans• availability and responsiveness is critical to
customer satisfaction
Business Problem• Logins took minutes to retrieve relational
access rights• Massive joins across millions of plans,
customers, admins, groups• Nightly batch production required 9 hours
and produced stale data
Solution and Benefits• Shifted authentication from Sybase to Neo4j• Moved resource graph to Neo4j• Replaced batch process with real-time login
response measured in milliseconds that delivers real-time data, vw yday’s snapshot
• Mitigated customer retention risks
Identity and Access Management
Telenor COMMUNICATIONS
SUBSCRIBED_BYCONTROLLED_BY
PART_OFUSER_ACCESS
Account
Customer
CustomerUser
Subscription
37
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Background• Top investment bank with $1+ trillion in assets• Using a relational database and Gemfire to
manage employee permissions to research document and application-service resources
• Permissions for new investment managers and traders provisioned manually
Business Problem• Lost an average of 5 days per new hire while
they waited to be granted access to hundreds of resources, each with its own permissions
• Replace an unsuccessful onboarding process implemented by a competitor
• Regulations left no room for error
Solution and Benefits• Store models, groups and entitlements in
Neo4j• Exceeded performance requirements• Major productivity advantage due to domain
fit• Graph visualization ease permissioning
process• Fewer compromises than with relational• Expanded Neo4j solution to online
brokerage
UBS FINANCIAL SERVICES
Identity and Access Management38
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INVESTIGATE
Revolving Debt
Number of Accounts
INVESTIGATE
Normal behavior
Fraud Detection with Discrete Analysis
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Revolving Debt
Number of Accounts
Normal behavior
Fraud Detection With Connected Analysis
Fraudulent pattern
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Background• Global financial services firm with trillions of
dollars in assets• Varying compliance and governance
considerations• Incredibly complex transaction systems, with
ever-growing opportunities for fraud
Business Problem • Needed to spot and prevent fraud detection in
real time, especially in payments that fall within “normal” behavior metrics
• Needed more accurate and faster credit risk analysis for payment transactions
• Needed to dramatically reduce chargebacks
Solution and Benefits• Lowered TCO by simplifying credit risk analysis
and fraud detection processes• Identify entities and connections uniquely• Saved billions by reducing chargebacks and
fraud• Enabled building real-time apps with non-
uniform data and no sparse tables or schema changes
London and New York Financial FINANCIAL SERVICES
Fraud Detection
s
41
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Background• Panama based lawyers Mossack & Fonseca
do business in hosting “letterbox companies”
• Suspected to support tax saving and organized crime
• Altogether: 2.6 TB, 11 milo files, 214.000 letter box companies
Business Problem • Goal to unravel chains Bank-Person–Client–
Address–Intermediaries – M&F• Earlier cases: spreadsheet based analysis
(back-and-forth) & pencil to extract such connections
• This case: sheer amount of data & arbitrarily chain length condemn such approaches to fail
Solution and Benefits• 400 journalists, investigate/update/share, 2
people with IT background• Identify connections quickly and easily• Fast Results wouldn‘t be possible without
GraphDB
Panama Papers Fraud Detection
Fraud Detection42
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How to Start?